@InProceedings{hulden:2017:CoNLL,
  author    = {Hulden, Mans},
  title     = {A phoneme clustering algorithm based on the obligatory contour principle},
  booktitle = {Proceedings of the 21st Conference on Computational Natural Language Learning (CoNLL 2017)},
  month     = {August},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {290--300},
  abstract  = {This paper explores a divisive hierarchical clustering algorithm based on the
	well-known Obligatory Contour Principle in phonology.  The purpose is twofold:
	to see if such an algorithm could be used for unsupervised classification of
	phonemes or graphemes in corpora, and to investigate whether this purported
	universal constraint really holds for several classes of phonological
	distinctive features.  The algorithm achieves very high accuracies in an
	unsupervised setting of inferring a consonant-vowel distinction, and also has a
	strong tendency to detect coronal phonemes in an unsupervised fashion.
	Remaining classes, however, do not correspond as neatly to phonological
	distinctive feature splits.  While the results offer only mixed support for a
	universal Obligatory Contour Principle, the algorithm can be very useful for
	many NLP tasks due to the high accuracy in revealing consonant/vowel/coronal
	distinctions.},
  url       = {http://aclweb.org/anthology/K17-1030}
}